Minimal important differences for fatigue patient reported

RESEARCH ARTICLE Open Access

Minimal important differences for fatiguepatient reported outcome measures—asystematic reviewÅsa Nordin1,2, Charles Taft1,3, Åsa Lundgren-Nilsson1,2 and Anna Dencker1,3*

Abstract

Background: Fatigue is the most frequent symptom reported by patients with chronic illnesses. As a subjectiveexperience, fatigue is commonly assessed with patient-reported outcome measures (PROMs). Currently, there are morethan 40 generic and disease-specific PROMs for assessing fatigue in use today. The interpretation of changes in PROMscores may be enhanced by estimates of the so-called minimal important difference (MID). MIDs are not fixed attributesof PROMs but rather vary in relation to estimation method, clinical and demographic characteristics of the study group,etc. The purpose of this paper is to compile published MIDs for fatigue PROMs, spanning diagnostic/patient groups andestimation methods, and to provide information relevant for appraising their appropriateness for use in specific clinicaltrials and in monitoring fatigue in defined patient groups in routine clinical practice.

Methods: A systematic search of three databases (Scopus, CINAHL and Cochrane) for studies published between January2000 to April 2015 using fatigue and variations of the term MID, e.g. MCID, MIC, etc. Two authors screened search hitsand extracted data independently. Data regarding MIDs, anchors used and study designs were compiled in tables.

Results: Included studies (n = 41) reported 60 studies or substudies estimating MID for 28 fatigue scales, subscales orsingle item measures in a variety of diagnostic groups and study designs. All studies used anchor-based methods, 21/60measures also included distribution-based methods and 17/60 used triangulation of methods. Both similarities anddissimilarities were seen within the MIDs.

Conclusions: Magnitudes of published MIDs for fatigue PROMs vary considerably. Information about the derivation offatigue MIDs is needed to evaluate their applicability and suitability for use in clinical practice and research.

Keywords: MID, Fatigue, PROM, Minimal important difference, Systematic review, MCID, MCII

BackgroundFatigue is among the most frequent complaints reported bypatients with chronic illnesses [1–4] and has far-ranging,often debilitating consequences on their wellbeing andphysical, emotional and social functioning [5]. Althoughthere is no consensus definition of fatigue, it is often de-scribed as ‘a persistent, overwhelming sense of tiredness,weakness or exhaustion resulting in a decreased capacityfor physical and⁄or mental work [6]. Fatigue is a subjectiveexperience and is commonly assessed by means of patient-

reported outcome measures (PROMs). PROMs are widelyused today in evaluating the effects of illness and treatmenton symptoms, functioning, and other outcomes from thepatient’s perspective [7].Currently, there are some 40 generic and disease-specific

PROMs for assessing fatigue in use today [8]. Most of thesefatigue measures have been evaluated regarding various as-pects of validity and reliability. Although these are import-ant psychometric properties reflecting the quality of themeasure, they are of little value in interpreting the meaningof scores derived from that measure [9]. Nonetheless, in-terpretation of scores, in particular changes in scores, is ofcritical concern in trials evaluating effects of treatmentsaimed at reducing fatigue, as well as in routine clinicalpractice in monitoring and managing fatigue in individual

* Correspondence: [email protected] Centre for Person-Centred Care (GPCC), Sahlgrenska Academy,University of Gothenburg, Gothenburg, Sweden3Institute of Health and Care Sciences, Sahlgrenska Academy, University ofGothenburg, Gothenburg, SwedenFull list of author information is available at the end of the article

© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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patients. In clinical trials, it has long been recognized thatconventional statistical significance testing provides infor-mation regarding the probability that an effect exists, notabout the meaningfulness of the size of the effect [10]. Inclinical practice, difficulties in evaluating and interpretingchanges in PROM scores often impinge on their usefulnessin informing clinical decision-making [11].The interpretation of changes in PROM scores may be

enhanced by estimates of the so-called minimal import-ant difference (MID). MID was originally defined over25 years ago as “the smallest difference in score in thedomain of interest which patients perceive as beneficialand which would mandate, in the absence of troublesomeside effects and excessive cost, a change in the patient’smanagement” [12]. During the past decades considerableresearch attention has been directed towards deriving MIDsfor PROMS. In this pursuit a variety of methods have beendeveloped and applied, but no clear consensus exists re-garding which method or methods are most suitable.To date, two main methods have been applied, namely

anchor-based approaches and distribution-based ap-proaches. Descriptions of these methods are beyond thescope of this paper and are summarized in detail else-where [13]. Briefly, anchor-based approaches use variousexternal criteria (patient-reported, physician-reported, orclinical anchors) to interpret whether a particular magni-tude of change is important. For example, a commonanchor-based method involves the use of global ratingscales (GRS) where MIDs are derived by comparing pa-tients’ self-ratings of change (e.g., “much worse”—“muchbetter”) to change in PROM scores. The MID is oftendefined as lying within the range of “slightly worse/better”on the GRS [9]. Distribution-based approaches rely on thestatistical characteristics of the distribution of scores inthe sample, in which the magnitude of change is generallyexpressed as a function of the standard deviation (SD) ofscores alone or in combination with the reliability of thePROM (standard error of the measurement (SEM)) [14].Various SD and SEM cut-off values have been proposedfor estimating MIDs, including ½ or 1/3 SD and 1–2SEM. Another commonly applied method is the use of ef-fect sizes (ES) or standardized response means (SRM),where change scores are divided by the SD at baseline orthe SD of change, respectively. The MID is often definedas change values lying within the range of 0.2-0.5. Adisadvantage to distribution-based approaches is that theydo not address the clinical importance of the change.Recent recommendations have proposed that as a first-line method multiple anchor-based approaches should beused, which, supported by distribution-based methods,may be triangulated to a single MID value or smallerrange of values [14–17].Although appealing for its simplicity, the idea of a sin-

gle, universal MID value for any particular PROM remains

elusive for a number of reasons. Firstly, different MIDestimation approaches have been shown to yield highlydisparate MIDs and hence triangulation (combining dif-ferent methods to estimate a MID) may be problematic[18]. Secondly, MIDs have also been shown to differ bypopulation and context [14]. For example, MIDs varyby diagnostic group, characteristics of the study sample,e.g., demographics and baseline levels; disease severity;treatment; choice of anchors [18, 19] as well as if MIDsgauge improvement versus deterioration [20]. This vari-ability suggests the need to understand how a particularMID value was determined in order to judge its appro-priateness for use in research for interpreting changeand/or computing sample sizes, or in clinical practicefor monitoring fatigue in specific patient groups [21].The purpose of this paper is to compile published

MIDs for fatigue PROMs, spanning diagnostic/patientgroups and estimation methods, and to provide informa-tion relevant for appraising their appropriateness for usein specific clinical trials and in monitoring fatigue in de-fined patient groups in routine clinical practice.

MethodsA systematic literature review where three databases(Scopus, CINAHL and Cochrane) were searched fromJanuary 2000 to April 2015 to identify studies withcalculated MIDs in fatigue scales, subscales and singleitem measures. The searches were limited to Englishlanguage (search string: “minimal clinical importantdifference*” OR “minimal important difference*” OR“minimal clinically important difference*” OR “minimallyimportant difference*” OR “clinical important improve-ment*” OR “clinically important improvement*” OR“minimal important clinical difference*” OR “minimallyimportant clinical difference*” OR ”responder defin-ition”) AND Fatigue). The search was augmented withscreening of article reference lists. All expressions in-cluding “difference/change/improvement” or equiva-lent, “important” as well as “minimal” or “clinical”, or“responder definition” were defined as MIDs. To facili-tate the reading all minimally important changes arecalled MIDs in this paper.

Selection of articlesInclusion criteria were reporting MIDs in text and/ortables for a fatigue scale, subscale or single item measure-ment of fatigue. Exclusion criteria were: reported MIDwas not derived directly in the study; insufficient informa-tion supplied about the study sample, study design and/ormethod for determining the MID; study sample < 18 years,not separate reporting of MIDs for a fatigue subscale andconference abstracts. Exclusion on title/abstract and onfull-text levels were done independently by two researchers(ÅN and AD), see Fig. 1.

Nordin et al. BMC Medical Research Methodology (2016) 16:62 Page 2 of 16

Data extractionTwo authors (ÅN and AD) extracted data regarding MIDsand methods used, including anchors used. The lastauthor (AD) checked all data extraction and preparedthe tables. To facilitate interpretation all MIDs are shownas absolute values and decimals are restricted to one sig-nificant number only, except for effect sizes. Some studiesreported standard deviation (SD) and confidence intervalsbut these are not shown in our tables or text. The fatiguemeasurements were identified as multidimensional scales,unidimensional scales or subscales, single item measure-ment or item bank scales.

ResultsThe literature search generated 177 articles (Fig. 1), ofwhich 41 met the inclusion criteria [22–62]. The mainreasons for exclusion were: reported MID was not derivedin the study; and inadequate information was suppliedabout the study sample, study design and/or method fordetermining the MID. Many different expressions wereused to name a small but important change in fatigue[13]. In this review we included studies using differentphrases for MID (see Table 1), e.g. “MID”, “MCID”,“MCII” or an equivalent expression, all referred to as MIDin this paper. Most of these expressions used some vari-ation of “difference/change/improvement” or equivalent,“important” as well as “minimal”. Some phrases also in-cluded “clinical”. Two studies used “responder definition”[43, 55], see Table 1. In two systematic reviews a phrasewithout “minimal” was used [59, 60] but the authors de-fined values for a small or minimal change.The included articles (n = 41) reported MIDs for 28

fatigue PROMs (characteristics shown in Table 2), result-ing in 60 studies/substudies of MIDs. The studies variedin sample size, diagnostic group, MID estimation ap-proach, study design, type of intervention and length offollow up. Sample sizes ranged from n = 40 to n = 2,583.

Sixteen different diagnoses were included in the reviewedstudies. Twenty-seven of the studies in the 41 articles werelongitudinal and follow-up periods ranged from two daysafter intervention to one year after baseline. An anchor-based approach alone was used in 39 of the 60 studies orsubstudies estimating MID, while the rest also used adistribution-based approach. Seventeen of these also in-cluded a method of triangulation to define MIDs. Twocross-sectional studies [33, 46] reported MIDs for sevenfatigue or vitality scales (MFI, FSS, MAF, CFS, VT/SF-36,FACIT-F and GRS). Other studies determined MIDs fortwo or more fatigue measures or subscales [28, 47, 48, 51,59–61]. Several PROMs had MIDs determined in a num-ber of different studies and several studies reported MIDsfor up to seven PROMs. Nevertheless, most MIDs werederived in single studies, with one study per PROM[22–27, 29–32, 34–43, 45, 49, 50, 52–58, 62], seeTable 3. Altogether, 60 studies or substudies estimatingMIDs for global change (not specified direction of change),improvement and/or deterioration are described in Table 3.In Table 3 all score changes are presented as positive values,regardless of the direction of change. Confidence intervalsand SDs (if derived in study) are not shown. Numbers arerounded to one decimal place.

Multidimensional scalesMultidimensional fatigue inventory (MFI), score 20–100Two cross-sectional studies [33, 46] derived MIDs forsystemic lupus erythematosus (SLE) and rheumatoidarthritis (RA) populations for the MFI total scale,using a patient global rating scale and interviews asanchors. MIDs ranged from 11.5 to 13.3 for globalchange and 6.8 to 9.6 for improvement and 9.5 and12.8 for deterioration.

Fatigue severity scale (FSS), score 1–7Three cross-sectional studies reporting MIDs for theFSS were identified [33, 46, 50]. Diagnostic groups in-cluded SLE, RA and multiple sclerosis (MS). Anchor-based approaches were applied in all the three studiesand a distribution-based approach (viz. effect size, ES, ofat least 0.25) was also applied in one [50]. Two used apatient global rating scale as an anchor [33, 46] whereasthe third used clinical anchors and baseline data from aclinical trial to establish MIDs [50] MIDs ranged from0.5 to 1.2 for global change, 0.08 to 0.4 for improvementand 1.0 to 1.2 for deterioration.

Multidimensional assessment of fatigue (MAF), score 1–50MID-estimates for the MAF in two cross-sectionalstudies with SLE and RA patients [33, 46] were estimatedto 5.0 and 9.2 for global change, 1.4 to 5.4 for improve-ment and 8.3 to 8.9 for worsening, using a patient globalrating scale.

Potentially relevant publications identified and screened for retrieval n = 177

Publications excluded on the basis of duplication, n = 25

Publications excluded on the basis of title or abstract, n = 79

Full text publications retrieved for more detailed evaluation, n = 73

Publications excluded after full-text screening, n = 32

Publications included in the review, n = 41

Fig. 1 Flowchart of selection of articles to include


Table 1 Included articles with reported fatigue MIDs, n = 41

First author/country Instrument/scale Term useda

Baró et al. 2011 [22]Spain

Perform Questionnaire Minimally important difference, MID

Bedard et al. 2013a [23]Canada

ESAS fatigue item Minimal clinically important difference, MCID

Bedard et al. 2013b [24]Canada

EORTC QLQ-30—Fatigue Scale Minimal important difference, MID

Bedard et al. 2014 [25]Canada

EORTC QLQ-30—Fatigue Scale Minimal important difference, MID

Bjorner et al. 2007 [26]USA, MOS-study

VT/SF-36 Minimally important difference, MID

Borghs et al. 2012 [27]Belgium

QOLIE-3 Energy/fatigue subscale Minimally important change, MIC

Cella et al. 2002 [28]USA

FACIT-Fatigue TOI-F Minimal clinically important difference, CID(MCID in short title)

Cella et al. 2005 [29]USA

FACT-Fatigue Minimally important difference, MID

Colangelo et al. 2009 [30]Canada

Fatigue VAS (0–100) Minimally important difference, MID

de Kleijn et al. 2011 [31]Netherlands

FAS Minimal (clinically) important difference, MCID

George & Pope 2011 [32]Canada

VAS fatigue (0–100) Minimal important difference, MID

Goligher et al. 2008 [33]Canada

MFI, FSS, MAF, CFS, FACIT-F, VT/SF-36, GRS Minimal important difference, MID

Khanna et al. 2008 [34]Canada


Kosinski et al. 2000 [35]USA

VT/SF-36 Minimally important change, MIC

Kvam et al. 2010 [36]Norway

EORTC QLQ-C30 Fatigue Subscale Minimal important difference, MID

Kwok and Pope 2010 [37]Canada


Lai et al. 2011 [38]USA

FACIT-Fatigue subscale Minimally important difference, MID

Lasch et al. 2009 [39]USA

SIS Energy/Fatigue and Mental Fatigue subscales Minimum important difference, MID

Maringwa et al. 2011a [40]17 countries

EORTC QLQ-C30 Fatigue Subscale Minimal clinically important difference, MCID

Maringwa et al. 2011b [41]12 countries

EORTC QLQ-C30 Fatigue Subscale Minimal important difference, MID

Mathias et al. 2009 [42]USA and Europe

ITP-PAC Minimally important difference, MID

Matza et al. 2013 [43]USA

FAsD Responder definition

Mills et al. 2012 [44]UK

NFI-MS Minimum clinically important difference, MCID

Patrick et al. 2003 [45]USA

FACT-An fatigue subscale Minimally important difference, MID

Pouchot et al. 2008 [46]Canada

MFI, FSS, MAF, CFS, FACIT-F, VT/SF-36, GRS Minimal clinically important difference, MCID

Purcell et al. 2010 [47]Australia

MFI subscales Minimal clinically importantdifference, MCID

Reddy et al. 2007 [48]USA

FACIT-Fatigue subscale ESAS fatigue item Clinically important improvement


Chalder fatigue scale (CFS), score 0–33The same two cross-sectional studies [33, 46] reportedMIDs for the CFS where MIDs for global change were 2.3–3.3; for improvement 0.7–1.4; and for deterioration 3.2–3.5.

Fatigue impact scale (FIS), score 0–160One cross-sectional study with MS patients [49] reportedMIDs for the FIS ranging from 9–24 points for the differ-ent patient and clinician rating anchors, with a mean of15.5 and SD 4.9. Distribution-based methods yielded MIDsranging between 4.8–17.3 (1–2 SEM; ± 1/3-1/2 SD).Triangulation of anchor and distribution-based methodsgave a MID range of 10–20 points.

Trial outcome index-fatigue (TOI-F), score 0–108One study [28] reported TOI-F MIDs using data fromthree separate cancer trials. Triangulation was used todetermine a MID, combining a patient-reported anchor,two physician-reported anchors (including response totreatment ratings), and one clinical anchor (haemoglobinlevel). MID estimates ranged from 4.8 to 26.6, and a sin-gle triangulated MID of 5.0 was recommended.

Perform questionnaire (PQ), score 12–60One longitudinal study [22] estimated the PQ MID incancer patients to be 3.7 for improvement. Triangulationwas used to estimate a recommended MID of 3.5.

Schwartz cancer fatigue scale (SCFS), score 3–30A longitudinal study of the SCFS using a patient-ratedanchor [51] reported MIDs for global change was 5.0;for improvement 2.1; and for deterioration 5.7 after atwo days follow-up.

Fatigue associated with depression questionnaire (FAsD),score 1–5MIDs for the FAsD were estimated in one longitudinalstudy [43] of patients with a clinical diagnosis of depres-sion ranging from 0.3 to 0.6 for improvement and 0.2–0.3for worsening after 6 weeks follow-up.

Neurological fatigue index for multiple sclerosis (NFI-MS),summary score 0–30One longitudinal study [44] using a patient global as-sessment of change reported MIDs for the NFI-MS; 2.5for the ten-item Summary scale, 2.4 for the Physicalscale (score range 0–24) and 0.8 for the Cognitive scale(score range 0–12).

Unidimensional scales or subscalesMultidimensional fatigue inventory (MFI) subscales, score 4–20A longitudinal study [47] derived MIDs in a cancerpopulation (pre and post radiotherapy) for the MFI fivesubscales. MIDs ranged between 1.4 to 2.4 depending on

Table 1 Included articles with reported fatigue MIDs, n = 41 (Continued)

Rendas-Baum et al. 2010 [49]Canada

FIS Minimally important difference, MID

Robinson et al. 2009 [50]USA

FSS Minimally important difference, MID

Schwartz et al. 2002 [51]USA

SCFS, POMS-F, single item Minimally important clinical difference, MICD

Schünemann et al. 2005 [52] CRQ/Fatigue subscale Minimal important difference, MID

Sekhon et al. 2010 [53]Canada


Spiegel et al. 2005 [54] VT/SF-36 Minimally clinically important difference, MCID

Twiss et al. 2010 [55]8 countries

U-FIS Responder definition, RD

Ward et al. 2015 [56]USA

VT/SF-36 Minimal clinically important improvement, MCII

Wells et al. 2007 [57]USA

Fatigue VAS (0–100) Minimal clinically important difference, MCID

Wheaton & Pope 2010 [58]Canada

Fatigue VAS (0–100) Minimal important difference, MID

Wyrwich et al. 2003 [59] VT/SF-36 CRQ/Fatigue subscale Clinically important difference, CID

Wyrwich et al. 2004 [60] VT/SF-36 CHQ/Fatigue subscale Clinically important difference, CID

Yost et al. 2011 [61]USA

PROMIS Fatigue (Fatigue-17, Fatigue-7) Minimally important difference, MID

Zeng et al. 2012 [62]7 countries

EORTC QLQ-C30 Fatigue Subscale Minimal clinically important difference, MCID

aAll expressions in this column are referred to as “MID” in the current study


subscale. A general MID for all MFI subscales was rec-ommended corresponding to 2 points.

Unidimensional fatigue impact scale (U-FIS), score 0–66One longitudinal study using EQ5D as an anchor[55] derived MIDs in an MS sample. U-FIS MIDscorresponded to 6.5 for improvement and 4.7 for

deterioration, and distribution-based MIDs between2.4 and 7.0.

Fatigue assessment scale (FAS), score 10–50MIDs for the FAS were reported in one longitudinalstudy of sarcoidosis patients using WHOQOL-BREF/Physical health domain and a ROC-curve as anchors as

Table 2 Overview of reviewed fatigue scales, subscales and single fatigue item with published MIDs, n = 28

Name of PROM Abbreviated name Numberof items

Score range Characteristics of scale

Chalder Fatigue Scale CFS 14 0–33 Multidimensional

Chronic Heart Failure Questionnaire, Fatigue subscale CHQ 4 1–7 Unidimensional subscaleNegative scorea

Chronic Respiratory Questionnaire, Fatigue subscale CRQ 4 1–7 Unidimensional subscaleNegative scorea

Edmonton Symptom Assessment System, Fatigue item ESAS Fatigue item 1 0–10 Single item

European Organization for Research and Treatmentof Cancer Quality of Life Questionnaire Core 30,Fatigue Subscale

EORTC QLQ-30Fatigue Subscale

3 0–100 Unidimensional subscale

FACIT-Fatigue Scale FACIT-Fatigue 13 0–52 Unidimensional scale/subscale,Negative scorea

FACT-An, Fatigue subscale FACT-An Fatigue 20 0–80 Unidimensional subscale

Fatigue Assessment Scale FAS 10 10–50 Unidimensional

Fatigue Associated with Depression Questionnaire FAsD 13 1–5 Multidimensional

Fatigue Impact Scale FIS 40 0–160 Multidimensional

Fatigue Severity Scale FSS 9 1–7 Multidimensional

Global RS GRS 1 0–10 Single item

Immune thrombocytopenic Purpura –PatientAssessment Questionnaire, Fatigue subscale

ITP-PAC 1 0–100 Single item

Multidimensional Assessment of Fatigue MAF 16 1–50 Multidimensional

Multidimensional Fatigue Inventory MFI 20 20–100 (4–20 ineach subscale)

Multidimensional, (5 subscales:GF, PF, RA, RM and MF)b

Neurological Fatigue Index for multiple sclerosis NFI-MS 12 0–30 in SS, 0–24 inPS and 0–12 in CS

Multidimensional,(3 scales: SS, PS and CS)c

Perform Questionnaire PQ 12 12–60 Multidimensional, Negative scorea

Profile of Mood States-Fatigue POMS-F 7 0–28 Unidimensional subscale

PROMIS Fatigue-17 Fatigue-17 17 17–85 Unidimensional

PROMIS Fatigue-7 Fatigue-7 7 7–35 Unidimensional

Quality of Life Inventory in Epilepsy,Energy/Fatigue subscale

QOLIE-31 4 0–100 Unidimensional subscaleNegative scorea

Schwartz Cancer Fatigue Scale SCFS 6 6–30 Multidimensional

SF-36 Vitality scale SF-VT 4 0–100 Unidimensional subscale

Sleep Impact Scale, Energy/Fatigue (E/F),Mental Fatigue (MF) subscales

SIS 5 (E/F)3 (MF)

0–100 Unidimensional subscalesNegative scoresa

Trial Outcome Index-Fatigue TOI-F 27 0–108 Multidimensional, Negative scorea

Unidimensional Fatigue Impact Scale U-FIS 22 0–66 Unidimensional

Visual Analogue Scale 0–10 VAS 0–10 1 0–10 Single item

Visual Analogue Scale 0–100 VAS 0–100 1 0–100 Single itemaNegative score = high values indicate low level of fatiguebGF General fatigue, PF Physical fatigue, RA Reduced activity, RM Reduced motivation. MF Mental fatiguecSS Summary scale, PS Physical scale and CS Cognitive scale


Table 3 Studies/substudies (n = 60) with reported MIDs for fatigue scales, subscales or single fatigue items. Study design and population are shown along with estimationmethod

Instrument/scale(score range)

Citation/Population Design Anchor-based MID Distribution-based MID

Triangulation MID

Anchor Global change(% of scale range)

Improved Worsened

Multidimensional scales

MFI(20–100)

Goligher et al. 2008SLE (n = 80)

Cross-sectional GRS (7-step)Paired comparisons

11.5 (14 %) 9.6 12.8

Pouchot et al. 2008RA (n = 61)


13.3 (17 %) 6.8 9.5

FSS(1–7)



0.6 (10 %) 0.08 1.2



1.2 (20 %) 0.4 1.0

Robinson et al. 2009MS (n = 249)

Cross-sectional Disease duration, Expanded DisabilityStatus Scale, Patient Assessment of MSImpact, MS Functional Composite

0.5–1.1 (8–18 %) ES 0.3–0.8 1

MAF(1–50)



5.0 (10 %) 1.4 8.9



9.2 (19 %) 5.4 8.3

CFS(0–33)



2.3 (7 %) 0.7 3.2



3.3 (10 %) 1.4 3.5

FIS(0–160)

Rendas-Baum et al.2010 MS (n = 184)

Cross-sectional Expanded Disability Status Scale (EDSS),SF-36, EQ-5D

9–2415.5 (10 %)

4.8 (1 SEM),9.6 (2 SEM)11.6 (1/3 SD),17.3 (½ SD)

10–20

TOI-F(0–108)

Cella et al. 2002Cancer (n = 2,583)

Cross-sectionalLongitudinal3 studies, follow-up: 3 d - 12 m

Performance status, haemoglobin level,response to treatment

4.8–26.6 (4–25 %) 4.2 (1 SEM),10.5 (½SD)

5.0

PQ(12–60)

Baró et al. 2011Cancer (n = 437)

LongitudinalFollow-up: 3 m

Haemoglobin level 3.7 3.5

SCFS(6–30)

Schwartz et al. 2001Cancer (n = 103)

LongitudinalFollow-up: 2 d

GRS (7-step) 5.0 (21 %) 2.1 5.7

FAsD(1–5)

Matza et al. 2013Depression (n = 96)

LongitudinalFollow-up: 6 w

BFI, ESS, CGI-S, Patient’s perceptionof change

0.3–0.6 0.2–0.3

NFI-MS(0–30, 0–24 and0–12 resp.)

Mills et al. 2012MS (n = 208)

LongitudinalFollow-up: 6–8 w

Global perceived change item (5-step) 2.5 (SS) (8 %)2.4 (PS) (10 %)0.8 (CS) (7 %)

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Table 3 Studies/substudies (n = 60) with reported MIDs for fatigue scales, subscales or single fatigue items. Study design and population are shown along with estimationmethod (Continued)

Unidimensional scales or subscales

MFI sbscales: GF,PF, RA, RM and MF(4–20)

Purcell et al. 2010Cancer (n = 210)

LongitudinalFollow-up: 6 wpost treatment

Score change pre- and post-radiotherapy GF: 2.1 (13 %)PF: 2.0 (13 %)RA: 2.4 (15 %)RM: 1.6 (10 %)MF: 1.4 (9 %)

2 for eachsubscale

U-FIS(0–66)

Twiss et al. 2010MS (n = 911)


EQ-5D 6.5 4.7 4.2–7.0(ES 0.3–0.5)2.4 (1 SEM)

FAS(10–50)

de Kleijn et al. 2011Sarcoidosis (n = 321)


WHOQOL-BREF/Physical health domain, ROC 3.5 (9 %) 3.0 3.8 4.2 (ES 0.5)3.6 (1 SEM)

4

SF-36 VT(0–100)

Bjorner et al. 2007Several diseaseconditions (n = 3,445)

Cross-sectional Regression analyses using age, gender, race,disease condition and functional outcomes

5/group level10/individual level



10.7 (11 %) 7.3 18.3

Kosinski et al. 2000RA (n = 693)


Patient global assessment, Physician globalassessment, pain, swelling, tenderness

4.9–11.1(5–11 %)



14.8 (15 %) 11.3 11.9

Spiegel et al. 2005Hepatitis C virus

Systematic reviewDelphi method

ES data from included studies ES of 0.2Range0.15–0.25

4.2Range 3–5

Ward et al. 2015RA (n = 249)

LongitudinalFollow-up: 1–4 m

HAQ, CES-D, Health transition item of SF36,Global transition item

11.0–20.0(11–20 %)

Wyrwich et al. 2003Chronic obstructivepulmonary disease

Delphi method Patient change scenarios andSF36 data

12.5

Wyrwich et al. 2004Coronary artery disease/congestive heart failure

Delphi method Patient change scenarios andSF36 data

18.8Range 18.8–25

FACIT-Fatigue(0–52)

Cella et al. 2002Cancer (n = 2,583)

Cross-sectionalLongitudinal3 d - 12 m

Performance status, haemoglobin level,response to treatment

3 (6 %) 3

Cella et al. 2005RA (n = 271)


VT/SF-36, MAF 3–4 (6–8 %) 4.10 (1 SEM)2.2–5.5(ES 0.2–0.5)

3–4



5.9 (11 %) 2.8 9.1

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Lai et al. 2011SLE (n = 254)


Physician-reported anchors (Physician GA) 3–7 (6–13 %) 2.7 (1 SEM)4.6 (1/3 SD),6.8 (½SD)

3–6



8.3 (16 %) 6.8 5.2

Reddy et al. 2007Cancer (n = 194)


Global Benefit Score (7 step) 10

FACT-An Fatigue(0–80)

Patrick et al. 2003Cancer (n = 375)

Longitudinal,Follow-up: pre andpost chemotherapy

Haemoglobin levelRegression analysis

4.2

POMS-F(0–28)



GRS (7-step) 5.6 (20 %) 2.1 5.7

EORTC QLQ-C30Fatigue Subscale(0–100)

Bedard et al. 2013bCancer (n = 276)


Overall QoL 24.5 19.7 (1 SEM)6–15(0.2–0.5 SD)

Bedard et al. 2014Cancer (n = 369)


Overall QoL 1–7Overall health anchor

13.6–17.3 1.8 (1 SEM)6.7–16.8(0.2–0.5 SD)

Kvam et al. 2010Multiple myeloma(n = 239)


Global rating of change(7-step but categorized into 3)

13.5 8.6

Maringwa et al. 2011aBrain cancer (n = 941)

Cross-sectionaland longitudinal

WHO Performance Status and MMSE 12.4 8.9 10.0 (1 SEM)

Maringwa et al. 2011bLung cancer (n = 812)

Cross-sectionaland longitudinal

Physician-rated WHOPS and weight change

14.1 5.7 11 (1 SEM)

Zeng et al. 2012Cancer (n = 93)


KPS clinical marker 11.4 7.8 3.0–3.1 (1 SEM)5.8–14–7(0.2–0.5 SD)

SIS(0–100)

Lasch et al. 2009MDD (n = 379)


Clinician rated tool (7-step) on severityand improvement

E/F: 11.9 (12 %)MF: 13.3 (13 %)

8.7 (½SD)10.6 (½SD)

CRQ(1–7)

Schünemann et al. 2005Chronic obstructivepulmonary disease

Systematic review CRQ data from5 studies, patient globalratings anchors and distributions basedMIDs

0.5–0.6 (8–10 %) 0.47–0.54(1 SEM)

0.5

Wyrwich et al. 2003Chronic obstructivepulmonary disease

Delphi method Patient change scenarios and CHQ data 2

CHQ(4–28)

Wyrwich et al. 2004Coronary artery disease/congestive heart failure

Delphi method Patient change scenarios andCHQ data

3Range 3–4

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QOLIE-31Energy/fatiguesubscale(0–100)

Borghs et al. 2012Epilepsy (n = 1,035)

Longitudinalstudy of 3 RCTsFollow-up: 12 w

Patient global impression of change(PGIC)Regression analysis

7.5 (8 %) 5.8 (0.3 ES)9.4 (1 SEM)

Single item measure

VAS FatigueSingle item(0–100)

Colangelo et al. 2009SLE (n = 202)

LongitudinalFollow-up: 7.5 m

Self-rated health (5 step) 13.9 9.1

George & Pope 2011Sjögren’s syndrome(n = 40)

LongitudinalFollow-up: ≤ 16 m


Kwok & Pope 2010PsA (n = 200)

LongitudinalFollow-up: ≤12 m


Sekhon et al. 2010Systematic sclerosis(n = 109)



Wells et al. 2007RA (n = 1,043)

LongitudinalFollow-up: 6–12 mDelphi method

HAQ, Patient Global assessment ofdisease and pain

6.7–17 (7–17 %) 10

Wheaton & Pope2010 SpA (n = 140)



VAS FatigueSingle item(0–10)

Khanna et al. 2008RA (n = 307)


Retrospective anchor (5-step) 0.8–1.1 1.1–1.3 Improved:ES = 0.39Worsened:ES = 0.44

GRS Single item(0–10)



1.3 (13 %) 0.3 1.5



2.0 (20 %) 0.9 1.5



GRS (7-step) 1.1 (11 %)

ESAS fatigueSingle item(0–10)

Bedard et al. 2013aCancer (n = 421)


Well-being 0.1–1.3 1.0–1.8 0.1 (1 SEM)0.5–1.4(0.2–0.5 SD)

Reddy et al. 2007Cancer (n = 194)


Global Benefit Score (7 step) 4

ITP-PAC(0–100)

Mathias et al. 2009ITP (n = 125)


Global assessment of change items(15-step)

15.0 (15 %) ES = 0.57

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PROMIS fatigue item bank scales

PROMISFatigue-17(17–85)

Yost et al. 2011Cancer (n = 101)

Cross-sectionaland longitudinalFollow-up: 6–12 w

23 anchor measures T-score MID:2.5–4.5Raw-score MID:4.0–8.0 (6–12 %)

Cross-sectional:ES 0.34–0.79Longitudinal:ES 0.27–0.52

PROMISFatigue-7(7–35)

Yost et al. 2011Cancer (n = 101)

Cross-sectionaland longitudinalFollow-up: 6–12 w

23 anchor measures T-score MID: 3.0–5.0Raw-score MID:2.0–3.0 (7–11 %)

Cross-sectional:ES 0.24–0.76Longitudinal:ES 0.24–0.51

GRS (7-step) = Global rating scale with 7 response categories: Much more fatigue, Somewhat more fatigue, A little bit more fatigue, About the same fatigue, A little bit less fatigue, Somewhat less fatigue, and Muchless fatiguePaired comparisons = Participants rated their fatigue in relation to another participantPsA Psoriatic arthritis, SpA Spondyloarthropathy

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well as distribution based methods [31]. MID ranged be-tween 3.0 and 4.2 and a triangulated MID-value of 4 wassuggested.

Vitality scale (VT) of the medical outcome study SF-36health survey (SF-36), score 0–100Eight studies [26, 33, 35, 46, 54, 56, 59, 60] determinedMIDs for the VT scale of the SF-36 using different de-signs and diagnostic groups; longitudinal with patient-and/or clinician rated anchors, cross-sectional usingpatient-rated anchors and systematic reviews using com-bined study data and expert panels. The MIDs rangedfrom 7.3 to 11.3 for improvement, 11.9 to 18.3 for wors-ening and 3.5 to 20, for all those with a global changeand 4.2 to 18.8 for a triangulated MID.

FACIT fatigue scale (FACIT-Fatigue), score 0–52Six cross-sectional or longitudinal studies [28, 29, 33, 38,46, 48] reported MID estimates derived in patients withcancer, SLE, or RA using patient or clinician-rated anchors.In these studies, MIDs varied from 3 to 8.3 irrespective ofdirection of change, 2.8 to 6.8 for improvement and 5.2 to9.1 for deterioration. Two of the studies [29, 38] combinedvarious distribution-based approaches (SEM, SD and ES),resulting in MIDs ranging between 2.2 and 6.8, and pre-sented triangulated MIDs ranging between 3 and 6.

FACT-an fatigue subscale (FACT-An Fatigue), score 0–80One longitudinal study [45] estimated a MID for im-provement of 4.2 in cancer patients using haemoglobinlevel as a clinical anchor and regression analysis tocalculate MID.

Profile of mood states short form fatigue subscale (POMS-F),score 0–28One longitudinal study reported MIDs for the POMS-Fusing a sample of cancer patients undergoing chemo-therapy [51]. A global MID of 5.6 points was determinedas well as separate MIDs for improvement (2.1 points)and deterioration (5.7 points).

European organization for research and treatment ofcancer quality of life questionnaire core 30 (EORTCQLQ-30)—fatigue scale, score 0–100Six cross-sectional and longitudinal studies [24, 25, 36,40, 41, 62] reported MIDs derived in a variety of cancerdiagnoses. MIDs were reported as 11.4 to 17.3 points forimprovement and 5.7–24.5 points for deterioration.Distribution-based MIDs ranged from 3.0 to 19.7.

Sleep impact scale (SIS), energy/fatigue and mental fatiguesubscales, score 0–100One longitudinal study [39] using a clinician-rated an-chor and a distribution-based method to assess change

at 8-week follow-up, reported MIDs derived in patientswith major depressive disorder (MDD). The anchor-based approach yielded a MID of 11.9 for the Energy/Fa-tigue subscale, whereas the distribution-based MID was8.7. The corresponding MIDs for the Mental Fatiguesubscales were 13.3 and 10.6, respectively.

Chronic respiratory questionnaire (CRQ), score 1–7Two systematic reviews [52, 59] used CRQ data fromearlier studies to determine MIDs for the CRQ/Fatiguesubscale and triangulated MIDs of 0.5 and 2 wereproposed. One of the reviews estimated MIDs between0.5–0.6 for global change and distribution-based MIDs of0.47–0.54 [52].

Chronic heart failure questionnaire (CHQ), score 4–28One systematic review using CHQ data and an expertpanel proposed a MID for the CHQ/Fatigue subscaleof 3–4 irrespective of direction and a triangulatedMID of 3 [60].

Quality of life inventory in Epilepsy (QOLIE-31), energy/fatiguesubscale, score 0–100One longitudinal study used 3 randomised controlledtrials to examine MID for the QOLIE-31/Energy/fatiguesubscale [27]. A MID of 7.5 was defined using a patientrating of change and regression analysis. Distribution-based MIDs ranged between 5.4 and 9.4.

Visual analogue scale (VAS), score 0–100 or 0–10Six longitudinal studies [30, 32, 37, 53, 57, 58] derivedMIDs for the VAS 0–100 and one [34] for the VAS 0–10in a variety of diagnostic groups. MIDs for the VAS-100ranged from 1.4 to 13.9 for improvement and 3.6 to 15.2for deterioration, while the global change varied between6.7 and 17. One study [57] determined a triangulatedMID of 10 using the Delphi method. MIDs for the VAS-10 ranged between 0.8 to 1.1 for improvement and 1.1to 1.3 for worsening, and were derived from three differ-ent anchors and at different follow-up times in three dif-ferent diagnostic groups (RA, SLE and cancer) [34].

Global rating scale (GRS), score 0–10MIDs for the single item GRS scale were determined inSLE, RA and cancer patients in two cross-sectional stud-ies [33, 46] and one longitudinal study [51], all using apatient global rating scale as an anchor. Global MIDsranged from 1.1 to 2.0, while MIDs for improvementwere 0.3 to 0.9 and for deterioration 1.5.

Edmonton symptom assessment system (ESAS) fatigue item,score 0–10Two longitudinal cancer studies [23, 48] identified MIDsfor the fatigue item in the ESAS scale. MIDs for


improvement ranged from 0.1 to 4 and between 1.0 and1.8 for worsening of fatigue. Distribution-based MIDsranged from 0.1 to 1.4.

Immune thrombocytopenic Purpura—Patient assessmentquestionnaire, (ITP-PAC) fatigue subscale, score 0–100One longitudinal study [42] assessed MIDs using patientimpression of change for the ITP-PAC/Fatigue subscale.Global change was defined as 15.0 or as an effect size of0.57.

PROMIS fatigue item bank scales17-item PROMIS fatigue (fatigue-17) and 7-item PROMISFatigue (Fatigue-7), score 17–85 and 7–35One study [61] derived MIDs for both the PROMISFatigue-17 and Fatigue-7 in patients with cancer. Thestudy used both cross-sectional and longitudinal data aswell as anchor-based and distribution-based methods.Distribution-based MIDs were reported as effect sizes.For the Fatigue-17, the ES ranged from 0.34–0.79 and0.27–0.52 for cross-sectional and longitudinal designs,respectively. Corresponding effect sizes for the Fatigue-7were 0.24–0.76 and 0.24–0.51. Triangulated raw scoreMIDs ranged from 4.0 to 8.0 for the Fatigue-17 and 2.0to 3.0 for the Fatigue-7 while t-score MIDs varied be-tween 2.5 to 4.5 for the Fatigue-17 and 3.0 to 5.0 for theFatigue-7.

DiscussionThis systematic review identified 41 studies reportingMIDs for 28 fatigue PROMs or subscales measuring fa-tigue, yielding a total of 60 studies or substudies estimat-ing MID. It is important to note that there are manymore fatigue PROMs available today than the 28 re-ported here. For example, a critical review of fatiguePROMs from 2009 [8] identified 39 such PROMs; how-ever, only 11 of these overlapped with PROMs in our re-view. This suggests that there are roughly 56 or morefatigue PROMs currently represented in the literature.Considering the importance attributed to MIDs forinterpreting the meaningfulness of change in PROMscores [9, 63], it is somewhat surprising that MIDs areavailable for only about half of all published fatiguePROMs. Moreover, few PROMs had MIDs that were de-termined in more than two studies and diagnosticgroups, and more than half of the PROMs had MIDsthat were derived in only one diagnostic group. Importantexceptions were the SF-36 Vitality scale (>8 diagnosticgroups/8 studies; the FACIT-Fatigue scale (4 diagnoses/6studies); the EORTC QLQ-C30 Fatigue subscale (6 cancerdiagnoses/6 studies); and the VAS-100 Fatigue (6 diagno-ses/6 studies). Considering that these scales are some ofthe most widely used and oldest PROMs in use today it isunsurprising that greater research attention has focused

on determining MIDs for these scales; however, it is note-worthy that so few separate studies reported MIDs forcommonly used generic fatigue PROMs, such as the MFI,FSS, FIS and FAS.Previous research has highlighted considerable variabil-

ity in MID values as a function of estimation method,population and context [14, 18, 19], suggesting the im-portance of considering such factors when appraising theappropriateness of published MIDs for use in clinical re-search and practice. In line with this, substantial variationwas observed in MID values for individual fatigue PROMsin this review. For example, MIDs for the SF-36 Fatiguescale ranged from as low as 4.2 to as high as 20.0 points(0–100 point scale) in studies varying in methodologies, an-chors, diagnostic groups and direction of change assessed.Similarly, MIDs for the VAS-100 Fatigue scale ranged from1.4 to 17. MIDs for the cancer-specific EORTC QLQ-C30fatigue scale also varied between 1.8 and 24.5 points (0–100scale) and those for the FACIT-Fatigue scale rangedbetween 6 and 16 (converted to percent), see Table 3.This wide variation in MIDs for individual fatiguescales suggests the importance of understanding howany particular MID was derived and of applying thisknowledge when appraising its appropriateness forinterpreting changes in fatigue scores.MID estimation methods varied considerably in the

identified studies and substudies. However, in accordancewith recent recommendations regarding methods for MIDestimation [14], nearly all studies applied an anchor-basedapproach, where at least one anchor was used. Patient glo-bal change ratings were by far the most common anchor,but even clinician-reported and clinical anchors wereimplemented. Where more than one anchor was appliedeither a range of values was generally reported or, as rec-ommended [14, 63, 64], values were often triangulated toa single or smaller range of MIDs. Distribution-basedmethods were used in about a third of the studies andonly in conjunction with anchor-based approaches. A fewstudies used a Delphi method (Table 3).In the studies using several anchors to determine MID

values, global MID ranges varied within single studiesfrom as little as two points (percent scores), in relationto the FACIT-Fatigue scale using patient-based anchors[29], to about 20 points for the TOI-F [28] using patient,clinician and clinical anchors. Interestingly, two studiesreporting MIDs for the SF-36 Vitality scale, using thesame diagnostic group (RA) but different anchors, yieldedtwo distinct ranges of MIDs. In the study by Kosinskiet al. [35], using patient and physician global assessmentsas anchors, MIDs ranged from 4.9–11.1, whereas a rangeof 11.0–20.0 was reported by Ward et al. [56] using theHAQ, CES-D and the SF-36 health transition item.Neither of these studies triangulated the range of values toa single MID or smaller range of values and hence these


wide ranges of MIDs are arguably of questionable practicalvalue for interpreting change in fatigue in RA patients asmeasured with the SF-36 Vitality.Triangulation was used in 17 substudies, of which 10

used more than two anchors. This method has been rec-ommended for consolidating MIDs derived from differ-ent methods to a single or small range of MID values[14]. However, it has been criticized [19] since it may inpractice involve the need to converge widely disparateMIDs derived using different estimation methods and di-verse anchors, which often represent very differentstakeholder perspectives. An example of a MID triangu-lated from a wide range of MIDs is the TOI-F [28] wherea MID range of 4.4–24.6 (percent scores) was triangu-lated to 5.0. Where MID ranges are smaller, the valueand applicability of the triangulated MID may be moreimmediately apparent. For example, Schünemann et al.[52] reported a MID range for the CRQ of 6.7–8.5(percent scores), derived from patient anchors, a system-atic review and distribution-based methods, which was tri-angulated to a MID of 6.7.A second factor known to influence variation in MID

values is the patient population in which the MID is de-termined. Variation by diagnostic group is exemplifiedby comparing MIDS from two studies, each using thesame estimation method (7-step global rating scale) andstudy design (cross-sectional) but different diagnosticgroups [33, 46]. One of the studies [33] determinedMIDs for seven different fatigue PROMs in patients withSLE and the other [46] did the same in patients withRA. Comparison of the global MIDs for the SLE and RApatients, shown in Table 3, shows consistently smallerMIDs for SLE versus RA across all seven PROMs. Itis noteworthy that most PROMs had MIDs that weredetermined in only one patient population and therelevance of these MIDs for use in other patient groupsthus remains unclear.A third factor influencing variation in MID values is

the context within which the MID is determined. Con-text issues concern, for example, characteristics of thepatient population, e.g., such as baseline state [65], dis-ease severity [66], and direction of change [13, 20], aswell as study design and intervention. For example, pa-tients with baseline scores indicating more severe fatiguemay value magnitudes of change in fatigue differentlythan those with less severe fatigue. Corroborating previ-ous research finding, MIDs for improvement differedfrom those for deterioration in all identified studies.MIDs tended to be larger for deterioration than im-provement, except in the EORTC QLQ-30 and VASFatigue item. MIDs for improvement were consistentlysmaller than global MIDs.A strength of this study is that reported MIDs for fa-

tigue scales or subscales were systematically compiled

and described. Assessment for inclusion or exclusionand data extraction from included studies was done in-dependently by two authors (ÅN and AD). A limitationis that the search period was restricted to studies from2000 onwards and search strings for the many variationson MID was also limited and therefore some studiesreporting MIDs for fatigue scales may not have beencaptured in the literature searches. Another limitation isthat the description of the study designs and results hadto be summarized and simplified in tables and informa-tion could be lost. Therefore, when evaluating MIDs theoriginal study/studies should be consulted.

ConclusionsMIDs vary substantially by estimation method, patientpopulation and context both across and within fatiguePROMs. In light of this variation, published MIDsshould be applied judiciously, after carefully consideringtheir applicability to characteristics of the study in ques-tion. The information provided in this paper may serveto aid researchers and clinicians in making informed de-cisions regarding the appropriateness of published MIDsfor their particular study and patients.

AbbreviationsES, effect size; GRS, global rating scale; ITP, immune thrombocytopenicpurpura; MCID, minimal clinical important difference; MCII, minimal clinicallyimportant improvement; MDD, major depressive disorder; MID, minimalimportant difference; MS, multiple sclerosis; PRO, patient reported outcome;PROM, patient reported outcome measure; PROMIS, patient-reported outcomesmeasurement information system; RA, rheumatoid arthritis; SD, standarddeviation; SEM, standard error of measurement; SLE, systemic lupuserythematosus; QoL, quality of life.

FundingThis study was funded by the University of Gothenburg Centre forPerson-Centred Care (GPCC).

Availability of data and materialsNot applicable.

Authors’ contributionÅN, CT and ÅLN planned the study. ÅN and AD performed the searches,screened all research hits and extracted the data. All authors contributed tothe manuscript writing. AD made the tables. All authors agreed on the finalversion of the manuscript.

Competing interestsThe authors declare that they have no competing interests.

Consent for publicationNot applicable.

Ethics approvalNot applicable.

Author details1Gothenburg Centre for Person-Centred Care (GPCC), Sahlgrenska Academy,University of Gothenburg, Gothenburg, Sweden. 2Institute of Neuroscienceand Physiology, Sahlgrenska Academy, University of Gothenburg,Gothenburg, Sweden. 3Institute of Health and Care Sciences, SahlgrenskaAcademy, University of Gothenburg, Gothenburg, Sweden.


Received: 23 December 2015 Accepted: 17 May 2016

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Minimal important differences for fatigue patient reported